Mon, 04 Jun 2018

Package GADMTools updated to version 2.2-1 with previous version 2.1-1 dated 2017-04-29

Title: Easy Use of 'GADM' Shapefiles
Description: Manipulate, assemble, export <http://www.gadm.org> shapefiles. Create choropleth, heatmaps, dots plot, proportional dots and more.
Author: Jean Pierre Decorps [aut, cre], Morgane Vallee [ctb]
Maintainer: Jean Pierre Decorps <jp.decorps@epiconcept.fr>

Diff between GADMTools versions 2.1-1 dated 2017-04-29 and 2.2-1 dated 2018-06-04

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More information about GADMTools at CRAN
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Package tangram updated to version 0.4 with previous version 0.3.2 dated 2017-10-02

Title: The Grammar of Tables
Description: Provides an extensible formula system to quickly and easily create production quality tables. The steps of the process are formula parser, statistical content generation from data, to rendering. Each step of the process is separate and user definable thus creating a set of building blocks for highly extensible table generation. A user is not limited by any of the choices of the package creator other than the formula grammar. For example, one could chose to add a different S3 rendering function and output a format not provided in the default package. Or possibly one would rather have Gini coefficients for their statistical content. Routines to achieve New England Journal of Medicine style, Lancet style and Hmisc::summaryM() statistics are provided. The package contains rendering for HTML5, Rmarkdown and an indexing format for use in tracing and tracking are provided.
Author: Shawn Garbett [aut, cre], Thomas Stewart [ctb], Jennifer Thompson [ctb], Frank Harrell [ctb]
Maintainer: Shawn Garbett <Shawn.Garbett@vumc.org>

Diff between tangram versions 0.3.2 dated 2017-10-02 and 0.4 dated 2018-06-04

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Package rres updated to version 1.1 with previous version 1.0 dated 2018-04-09

Title: Realized Relatedness Estimation and Simulation
Description: Functions for studying realized genetic relatedness between people. Users will be able to simulate inheritance patterns given pedigree structures, generate SNP marker data given inheritance patterns, and estimate realized relatedness between pairs of individuals using SNP marker data. See Wang (2017) <doi:10.1534/genetics.116.197004>. This work was supported by National Institutes of Health grants R37 GM-046255.
Author: Bowen Wang
Maintainer: Bowen Wang <bowenwang7@gmail.com>

Diff between rres versions 1.0 dated 2018-04-09 and 1.1 dated 2018-06-04

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Package KRIS updated to version 1.1.1 with previous version 1.0.3 dated 2018-05-07

Title: Keen and Reliable Interface Subroutines for Bioinformatic Analysis
Description: Provides useful functions which are needed for bioinformatic analysis such as calculating linear principal components from numeric data and Single-nucleotide polymorphism (SNP) dataset, calculating fixation index (Fst) using Hudson method, creating scatter plots in 3 views, handling with PLINK binary file format, detecting rough structures and outliers using unsupervised clustering, and calculating matrix multiplication in the faster way for big data.
Author: Kridsadakorn Chaichoompu [aut, cre], Kristel Van Steen [aut], Fentaw Abegaz [aut], Sissades Tongsima [aut], Philip James Shaw [aut], Anavaj Sakuntabhai [aut], Luisa Pereira [aut]
Maintainer: Kridsadakorn Chaichoompu <kridsadakorn@biostatgen.org>

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New package gdm with initial version 1.3.10
Package: gdm
Type: Package
Title: Generalized Dissimilarity Modeling
Version: 1.3.10
Date: 2018-06-04
Author: Glenn Manion, Matthew Lisk, Simon Ferrier, Diego Nieto-Lugilde, Karel Mokany, Matthew C. Fitzpatrick
Maintainer: Matthew C. Fitzpatrick <mfitzpatrick@umces.edu>
Description: A toolkit with functions to fit, plot, and summarize Generalized Dissimilarity Models (Ferrier et al. 2007, <doi:10.1111/j.1472-4642.2007.00341.x>).
License: GPL-2
Depends: R (>= 2.15.2), raster, foreach, doParallel, parallel
LinkingTo: Rcpp
Imports: Rcpp (>= 0.10.4), reshape2, vegan
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: yes
Packaged: 2018-06-04 18:34:03 UTC; mlisk
Repository: CRAN
Date/Publication: 2018-06-04 21:54:27 UTC

More information about gdm at CRAN
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Package blockmodeling updated to version 0.3.1 with previous version 0.3.0 dated 2018-04-11

Title: Generalized and Classical Blockmodeling of Valued Networks
Description: This is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: Žiberna (2007)<doi:10.1016/j.socnet.2006.04.002>, Žiberna (2008)<doi:10.1080/00222500701790207>, Žiberna (2014)<doi:10.1016/j.socnet.2014.04.002>.
Author: Aleš Žiberna [aut, cre]
Maintainer: Aleš Žiberna <ales.ziberna@gmail.com>

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Package leaflet updated to version 2.0.1 with previous version 2.0.0 dated 2018-04-20

Title: Create Interactive Web Maps with the JavaScript 'Leaflet' Library
Description: Create and customize interactive maps using the 'Leaflet' JavaScript library and the 'htmlwidgets' package. These maps can be used directly from the R console, from 'RStudio', in Shiny applications and R Markdown documents.
Author: Joe Cheng [aut, cre], Bhaskar Karambelkar [aut], Yihui Xie [aut], Hadley Wickham [ctb], Kenton Russell [ctb], Kent Johnson [ctb], Barret Schloerke [ctb], jQuery Foundation and contributors [ctb, cph] (jQuery library), Vladimir Agafonkin [ctb, cph] (Leaflet library), CloudMade [cph] (Leaflet library), Leaflet contributors [ctb] (Leaflet library), Leaflet Providers contributors [ctb, cph] (Leaflet Providers plugin), Brandon Copeland [ctb, cph] (leaflet-measure plugin), Joerg Dietrich [ctb, cph] (Leaflet.Terminator plugin), Benjamin Becquet [ctb, cph] (Leaflet.MagnifyingGlass plugin), Norkart AS [ctb, cph] (Leaflet.MiniMap plugin), L. Voogdt [ctb, cph] (Leaflet.awesome-markers plugin), Daniel Montague [ctb, cph] (Leaflet.EasyButton plugin), Kartena AB [ctb, cph] (Proj4Leaflet plugin), Robert Kajic [ctb, cph] (leaflet-locationfilter plugin), Mapbox [ctb, cph] (leaflet-omnivore plugin), Michael Bostock [ctb, cph] (topojson), RStudio [cph]
Maintainer: Joe Cheng <joe@rstudio.com>

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Package ipeaData updated to version 0.0.2 with previous version 0.0.1 dated 2018-05-11

Title: Getting Data from IPEADATA
Description: Access data from IPEA (Instituto de Pesquisa Economica Aplicada) hosted at <http://www.ipeadata.gov.br>. It gets metadata and values for all series on the website.
Author: Gustavo Coelho [aut, cre], Lucas Mation [aut]
Maintainer: Gustavo Coelho <gustavo.coelho@ipea.gov.br>

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Package CePa updated to version 0.6 with previous version 0.5 dated 2012-09-11

Title: Centrality-Based Pathway Enrichment
Description: Use pathway topology information to assign weight to pathway nodes.
Author: Zuguang Gu
Maintainer: Zuguang Gu <jokergoo@gmail.com>

Diff between CePa versions 0.5 dated 2012-09-11 and 0.6 dated 2018-06-04

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New package rwc with initial version 1.11
Package: rwc
Type: Package
Title: Random Walk Covariance Models
Version: 1.11
Date: 2018-06-04
Author: Ephraim M. Hanks
Depends: R (>= 2.10), raster, Matrix, mvtnorm, MASS
Maintainer: Ephraim M. Hanks <hanks@psu.edu>
Description: Code to facilitate simulation and inference when connectivity is defined by underlying random walks. Methods for spatially-correlated pairwise distance data are especially considered. This provides core code to conduct analyses similar to that in Hanks and Hooten (2013) <doi:10.1080/01621459.2012.724647>.
License: GPL-2
NeedsCompilation: no
Packaged: 2018-06-04 17:32:33 UTC; ephraim
Repository: CRAN
Date/Publication: 2018-06-04 18:23:43 UTC

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Package RRreg updated to version 0.6.8 with previous version 0.6.7 dated 2018-04-04

Title: Correlation and Regression Analyses for Randomized Response Data
Description: Univariate and multivariate methods to analyze randomized response (RR) survey designs (e.g., Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69, <doi:10.2307/2283137>). Besides univariate estimates of true proportions, RR variables can be used for correlations, as dependent variable in a logistic regression (with or without random effects), or as predictors in a linear regression (Heck, D. W., & Moshagen, M. (2018). RRreg: An R package for correlation and regression analyses of randomized response data. Journal of Statistical Software, 85(2), 1–29, <doi:10.18637/jss.v085.i02>). For simulations and the estimation of statistical power, RR data can be generated according to several models. The implemented methods also allow to test the link between continuous covariates and dishonesty in cheating paradigms such as the coin-toss or dice-roll task (Moshagen, M., & Hilbig, B. E. (2017). The statistical analysis of cheating paradigms. Behavior Research Methods, 49, 724–732, <doi:10.3758/s13428-016-0729-x>).
Author: Daniel W. Heck [aut, cre], Morten Moshagen [aut]
Maintainer: Daniel W. Heck <heck@uni-mannheim.de>

Diff between RRreg versions 0.6.7 dated 2018-04-04 and 0.6.8 dated 2018-06-04

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Package pcalg updated to version 2.6-0 with previous version 2.5-0 dated 2017-07-12

Title: Methods for Graphical Models and Causal Inference
Description: Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Author: Markus Kalisch [aut, cre], Alain Hauser [aut], Martin Maechler [aut], Diego Colombo [ctb], Doris Entner [ctb], Patrik Hoyer [ctb], Antti Hyttinen [ctb], Jonas Peters [ctb], Nicoletta Andri [ctb], Emilija Perkovic [ctb], Preetam Nandy [ctb], Philipp Ruetimann [ctb], Daniel Stekhoven [ctb], Manuel Schuerch [ctb], Marco Eigenmann [ctb]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>

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Package np updated to version 0.60-8 with previous version 0.60-7 dated 2018-05-01

Title: Nonparametric Kernel Smoothing Methods for Mixed Data Types
Description: Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <http://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <http://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <http://www.sharcnet.ca>).
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]
Maintainer: Jeffrey S. Racine <racinej@mcmaster.ca>

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Package mixdist updated to version 0.5-5 with previous version 0.5-4 dated 2011-10-23

Title: Finite Mixture Distribution Models
Description: Fit finite mixture distribution models to grouped data and conditional data by maximum likelihood using a combination of a Newton-type algorithm and the EM algorithm.
Author: Peter Macdonald <pdmmac@mcmaster.ca>, with contributions from Juan Du <duduyy@hotmail.com>
Maintainer: Peter Macdonald <pdmmac@mcmaster.ca>

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Package bootRes updated to version 1.2.4 with previous version 1.2.3 dated 2012-11-27

Title: Bootstrapped Response and Correlation Functions
Description: Bootstrapped correlation and response functions are widely used in dendrochronology to calibrate tree-ring proxy data against multiple instrumental time series of climatic variables. With this package, we provide functionality similar to DENDROCLIM2002 (Biondi and Waikul (2004) <10.1016/j.cageo.2003.11.004>). A full description with examples is given in Zang and Biondi (2013) <10.1016/j.dendro.2012.08.001>.
Author: Christian Zang
Maintainer: Christian Zang <christian.zang@wzw.tum.de>

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New package ssh with initial version 0.2
Package: ssh
Type: Package
Title: Secure Shell (SSH) Client for R
Version: 0.2
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Description: Connect to a remote server over SSH to transfer files via SCP, setup a secure tunnel, or run a command or script on the host while streaming stdout and stderr directly to the client.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: libssh (the original, not libssh2)
RoxygenNote: 6.0.1.9000
Imports: getPass
Suggests: knitr, rmarkdown, spelling, sys, testthat, mongolite
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-05-26 22:40:40 UTC; jeroen
Repository: CRAN
Date/Publication: 2018-06-04 17:43:04 UTC

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Package RSAGA updated to version 1.1.1 with previous version 1.1.0 dated 2018-05-17

Title: SAGA Geoprocessing and Terrain Analysis
Description: Provides access to geocomputing and terrain analysis functions of the geographical information system (GIS) 'SAGA' (System for Automated Geoscientific Analyses) from within R by running the command line version of SAGA. This package furthermore provides several R functions for handling ASCII grids, including a flexible framework for applying local functions (including predict methods of fitted models) and focal functions to multiple grids. SAGA GIS is available under GPLv2 / LGPLv2 licence from <http://sourceforge.net/projects/saga-gis/>.
Author: Alexander Brenning [aut, cre] (<https://orcid.org/0000-0001-6640-679X>), Donovan Bangs [aut], Marc Becker [aut], Patrick Schratz [ctb] (<https://orcid.org/0000-0003-0748-6624>), Fabian Polakowski [ctb]
Maintainer: Alexander Brenning <alexander.brenning@uni-jena.de>

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Package RmarineHeatWaves updated to version 0.17.0 with previous version 0.16.1 dated 2018-02-28

Title: Detect Marine Heat Waves and Marine Cold Spells
Description: Given a time series of daily temperatures, the package provides tools to detect extreme thermal events, including marine heat waves, and to calculate the exceedances above or below specified threshold values. It outputs the properties of all detected events and exceedances.
Author: Albertus J. Smit [aut, cre] (R implementation.), Eric C. J. Oliver [aut] (The brain behind the Python implementation.), Robert W. Schlegel [ctb] (Graphical and data summaries.)
Maintainer: Albertus J. Smit <albertus.smit@gmail.com>

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Package qrcmNP updated to version 0.1.2 with previous version 0.1.0 dated 2017-09-22

Title: Nonlinear and Penalized Quantile Regression Coefficients Modeling
Description: Nonlinear and Penalized parametric modeling of quantile regression coefficient functions. Frumento P and Bottai M (2016) <doi:10.1111/biom.12410>.
Author: Gianluca Sottile [aut, cre]
Maintainer: Gianluca Sottile <gianluca.sottile@unipa.it>

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Package pkr updated to version 0.1.2 with previous version 0.1.1 dated 2017-07-10

Title: Pharmacokinetics in R
Description: Conduct a noncompartmental analysis as closely as possible to the most widely used commercial software for pharmacokinetic analysis, i.e. 'Phoenix(R) WinNonlin(R)' <https://www.certara.com/software/pkpd-modeling-and-simulation/phoenix-winnonlin/>. Some features are 1) CDISC SDTM terms 2) Automatic slope selection with the same criterion of WinNonlin(R) 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107).
Author: Kyun-Seop Bae [aut], Jee Eun Lee [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>

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Package onewaytests updated to version 1.7 with previous version 1.6 dated 2018-01-30

Title: One-Way Tests in Independent Groups Designs
Description: Performs one-way tests in independent groups designs, pairwise comparisons, graphical approaches, assesses variance homogeneity and normality of data in each group via tests and plots.
Author: Osman Dag [aut, cre], Anil Dolgun [aut], N. Meric Konar [aut]
Maintainer: Osman Dag <osman.dag@hacettepe.edu.tr>

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Package LPWC updated to version 0.99.3 with previous version 0.99.2 dated 2018-04-12

Title: Lag Penalized Weighted Correlation for Time Series Clustering
Description: Computes a time series distance measure for clustering based on weighted correlation and introduction of lags. The lags capture delayed responses in a time series dataset. The timepoints must be specified. T. Chandereng, A. Gitter (2018) <doi:10.1101/292615>.
Author: Thevaa Chandereng [cre, aut], Anthony Gitter [aut]
Maintainer: Thevaa Chandereng <chandereng@wisc.edu>

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Package IsoplotR updated to version 1.3 with previous version 1.2 dated 2018-05-01

Title: Statistical Toolbox for Radiometric Geochronology
Description: Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington' and 'Ludwig' approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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More information about IsoplotR at CRAN
Permanent link

New package GREP2 with initial version 0.99.9
Package: GREP2
Type: Package
Title: GEO RNA-Seq Experiments Processing Pipeline
Version: 0.99.9
Authors@R: c(person("Naim Al", "Mahi", role = c("cre", "aut"), email = "mahina@mail.uc.edu"), person("Mario", "Medvedovic", role = c("aut", "ctb")))
Maintainer: Naim Al Mahi <mahina@mail.uc.edu>
Description: An R based pipeline to download and process Gene Expression Omnibus (GEO) RNA-seq data. For a given GEO series accession ID, this pipeline generates metadata, both gene and transcript level counts, and quality control (QC) report.
Depends: R (>= 3.4.0)
Imports: XML, rentrez, RCurl, GEOquery, Biobase, parallel, tximport, EnsDb.Hsapiens.v86, EnsDb.Rnorvegicus.v79, EnsDb.Mmusculus.v79, AnnotationDbi, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, GenomicFeatures, utils
Suggests: knitr, rmarkdown
SystemRequirements: SRAtoolkit, Salmon, Java, FastQC, MultiQC
URL: https://github.com/uc-bd2k/GREP2
BugReports: https://github.com/uc-bd2k/GREP2/issues
License: GPL-3
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-03 00:36:25 UTC; naim
Author: Naim Al Mahi [cre, aut], Mario Medvedovic [aut, ctb]
Repository: CRAN
Date/Publication: 2018-06-04 17:44:00 UTC

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Package glmnetcr updated to version 1.0.4 with previous version 1.0.3 dated 2017-09-07

Title: Fit a Penalized Constrained Continuation Ratio Model for Predicting an Ordinal Response
Description: Penalized methods are useful for fitting over-parameterized models. This package includes functions for restructuring an ordinal response dataset for fitting continuation ratio models for datasets where the number of covariates exceeds the sample size or when there is collinearity among the covariates. The glmnet fitting algorithm is used to fit the continuation ratio model after data restructuring.
Author: Kellie J. Archer
Maintainer: Kellie J. Archer <archer.43@osu.edu>

Diff between glmnetcr versions 1.0.3 dated 2017-09-07 and 1.0.4 dated 2018-06-04

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More information about glmnetcr at CRAN
Permanent link

Package autovarCore updated to version 1.0-4 with previous version 1.0-2 dated 2018-01-29

Title: Automated Vector Autoregression Models and Networks
Description: Automatically find the best vector autoregression models and networks for a given time series data set. 'AutovarCore' evaluates eight kinds of models: models with and without log transforming the data, lag 1 and lag 2 models, and models with and without weekday dummy variables. For each of these 8 model configurations, 'AutovarCore' evaluates all possible combinations for including outlier dummies (at 2.5x the standard deviation of the residuals) and retains the best model. Model evaluation includes the Eigenvalue stability test and a configurable set of residual tests. These eight models are further reduced to four models because 'AutovarCore' determines whether adding weekday dummies improves the model fit.
Author: Ando Emerencia [aut, cre]
Maintainer: Ando Emerencia <ando.emerencia@gmail.com>

Diff between autovarCore versions 1.0-2 dated 2018-01-29 and 1.0-4 dated 2018-06-04

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Package tseries updated to version 0.10-45 with previous version 0.10-44 dated 2018-04-15

Title: Time Series Analysis and Computational Finance
Description: Time series analysis and computational finance.
Author: Adrian Trapletti [aut], Kurt Hornik [aut, cre], Blake LeBaron [ctb] (BDS test code)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between tseries versions 0.10-44 dated 2018-04-15 and 0.10-45 dated 2018-06-04

 ChangeLog   |   48 +++---------------------------------------------
 DESCRIPTION |    8 ++++----
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 3 files changed, 9 insertions(+), 51 deletions(-)

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Package Compositional updated to version 3.1 with previous version 3.0 dated 2018-05-24

Title: Compositional Data Analysis
Description: Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. The standard textbook for such data is John Aitchison's (1986). "The statistical analysis of compositional data". Chapman & Hall.
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut]
Maintainer: Michail Tsagris <mtsagris@yahoo.gr>

Diff between Compositional versions 3.0 dated 2018-05-24 and 3.1 dated 2018-06-04

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Package beepr updated to version 1.3 with previous version 1.2 dated 2015-06-13

Title: Easily Play Notification Sounds on any Platform
Description: The main function of this package is beep(), with the purpose to make it easy to play notification sounds on whatever platform you are on. It is intended to be useful, for example, if you are running a long analysis in the background and want to know when it is ready.
Author: Rasmus Bååth [aut, cre], Amanda Dobbyn [ctb]
Maintainer: Rasmus Bååth <rasmus.baath@gmail.com>

Diff between beepr versions 1.2 dated 2015-06-13 and 1.3 dated 2018-06-04

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Package spatialwarnings updated to version 1.1 with previous version 1.0 dated 2017-11-03

Title: Spatial Early Warning Signals of Ecosystem Degradation
Description: Tools to compute and assess significance of early-warnings signals (EWS) of ecosystem degradation on raster data sets. EWS are metrics derived from the observed spatial structure of an ecosystem -- e.g. spatial autocorrelation -- that increase before an ecosystem undergoes a non-linear transition (Kefi et al. (2014) <doi:10.1371/journal.pone.0092097>).
Author: Alain Danet, Alexandre Genin, Vishwesha Guttal, Sonia Kefi, Sabiha Majumder, Sumithra Sankaran, Florian Schneider
Maintainer: Alexandre Genin <alexandre.genin@univ-montp2.fr>

Diff between spatialwarnings versions 1.0 dated 2017-11-03 and 1.1 dated 2018-06-04

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New package rcane with initial version 1.0
Package: rcane
Type: Package
Title: Different Numeric Optimizations to Estimate Parameter Coefficients
Version: 1.0
Date: 2018-06-01
Author: Akshay Suresh, Siddhesh Acharekar, Hsiangwei Chao, Shiva Yogi Biradar
Maintainer: Akshay Suresh<suresh.aks@husky.neu.edu>
Description: There are different numeric optimizations which are used in order to estimate coefficients in models such as linear regression and neural networks. This package covers parameter estimation in linear regression using different methods such as batch gradient descent, stochastic gradient descent, minibatch gradient descent and coordinate descent. Kiwiel, Krzysztof C (2001) <doi:10.1007/PL00011414> Yu Nesterov (2004) <ISBN:1-4020-7553-7> Ferguson, Thomas S (1982) <doi:10.1080/01621459.1982.10477894> Zeiler, Matthew D (2012) <arXiv:1212.5701> Wright, Stephen J (2015) <arXiv:1502.04759>.
License: MIT + file LICENSE
RoxygenNote: 6.0.1.9000
Suggests: testthat, knitr, rmarkdown, stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-01 16:16:00 UTC; sures
Repository: CRAN
Date/Publication: 2018-06-04 09:03:22 UTC

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Package ranger updated to version 0.10.1 with previous version 0.10.0 dated 2018-05-29

Title: A Fast Implementation of Random Forests
Description: A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.
Author: Marvin N. Wright [aut, cre], Stefan Wager [ctb], Philipp Probst [ctb]
Maintainer: Marvin N. Wright <cran@wrig.de>

Diff between ranger versions 0.10.0 dated 2018-05-29 and 0.10.1 dated 2018-06-04

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 13 files changed, 65 insertions(+), 64 deletions(-)

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New package AdaSampling with initial version 1.0
Package: AdaSampling
Type: Package
Title: Adaptive Sampling for Positive Unlabeled and Label Noise Learning
Version: 1.0
Author: Pengyi Yang & Dinuka Perera
Maintainer: Pengyi Yang <yangpy7@gmail.com>
Description: Implements the adaptive sampling procedure, a framework for both positive unlabeled learning and learning with class label noise. Yang, P., Ormerod, J., Liu, W., Ma, C., Zomaya, A., Yang, J. (2018) <doi:10.1109/TCYB.2018.2816984>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.4.0)
LazyData: true
Imports: caret (>= 6.0-78) , class (>= 7.3-14), e1071 (>= 1.6-8), stats, MASS
BugReports: https://github.com/PengyiYang/AdaSampling/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/PengyiYang/AdaSampling/
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-01 22:01:42 UTC; pengyiyang
Repository: CRAN
Date/Publication: 2018-06-04 09:19:52 UTC

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New package wISAM with initial version 0.2.8
Package: wISAM
Type: Package
Title: Weighted Inbred Strain Association Mapping
Version: 0.2.8
Author: Robert W. Cort <rcorty@gmail.com>
Maintainer: Robert W. Cort <rcorty@gmail.com>
Description: In the course of a genome-wide association study, the situation often arises that some phenotypes are known with greater precision than others. It could be that some individuals are known to harbor more micro-environmental variance than others. In the case of inbred strains of model organisms, it could be the case that more organisms were observed from some strains than others, so the strains with more organisms have better-estimated means. Package 'wISAM' handles this situation by allowing for weighting of each observation according to residual variance. Specifically, the 'weight' parameter to the function conduct_scan() takes the precision of each observation (one over the variance).
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.0.0)
LazyData: true
Suggests: testthat
RoxygenNote: 6.0.1
Imports: methods, MASS
NeedsCompilation: no
Packaged: 2018-05-31 17:18:15 UTC; rcorty
Repository: CRAN
Date/Publication: 2018-06-04 08:12:54 UTC

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New package spacesRGB with initial version 1.0-4
Package: spacesRGB
Type: Package
Title: Standard and User-Defined RGB Color Spaces, with Conversion Between RGB and CIE XYZ
Version: 1.0-4
Encoding: UTF-8
Date: 2018-05-31
Author: Glenn Davis [aut,cre]
Maintainer: Glenn Davis <gdavis@gluonics.com>
Description: Standard RGB spaces included are sRGB, 'Adobe' RGB, and 'ProPhoto' RGB. User-defined RGB spaces are also possible.
License: GPL (>= 3)
LazyLoad: yes
LazyData: yes
Depends: R (>= 2.13.0)
Suggests: microbenchmark
Repository: CRAN
NeedsCompilation: no
Packaged: 2018-06-01 00:56:07 UTC; Glenn
Date/Publication: 2018-06-04 08:47:57 UTC

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New package readabs with initial version 0.2.1
Package: readabs
Type: Package
Title: Read 'Excel' Files from the Australian Bureau of Statistics into Tidy Data Sets
Version: 0.2.1
Authors@R: c( person("Zoe", "Meers", role = c("aut", "cre"), email = "zoe.meers@sydney.edu.au"), person("Jaron", "Lee", role = c("aut"), email = "jaron.lee@sydney.edu.au"))
Maintainer: Zoe Meers <zoe.meers@sydney.edu.au>
Description: Reads files from the Australian Bureau of Statistics <https://www.abs.gov.au/> into clean, tidy data sets.
Date: 2018-05-30
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: readxl, dplyr, tidyr, sjmisc, rsdmx, readr, stringr
URL: https://github.com/zmeers/readabs
BugReports: https://github.com/zmeers/readabs/issues
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat
NeedsCompilation: no
Packaged: 2018-05-31 23:59:33 UTC; zmeers
Author: Zoe Meers [aut, cre], Jaron Lee [aut]
Repository: CRAN
Date/Publication: 2018-06-04 08:37:55 UTC

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New package nnTensor with initial version 0.99.1
Package: nnTensor
Type: Package
Title: Non-Negative Tensor Decomposition
Version: 0.99.1
Date: 2018-06-01
Author: Koki Tsuyuzaki, Manabu Ishii, Itoshi Nikaido
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>
Suggests: testthat
Depends: R (>= 3.4.0), fields, rTensor, plot3D, tagcloud
Imports: methods
Description: Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) <doi:10.1002/9780470747278> and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
License: Artistic-2.0
URL: https://github.com/rikenbit/nnTensor
NeedsCompilation: no
Packaged: 2018-06-01 00:42:22 UTC; tsuyusakikouki
Repository: CRAN
Date/Publication: 2018-06-04 08:48:01 UTC

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New package CVglasso with initial version 1.0
Package: CVglasso
Type: Package
Title: Lasso Penalized Precision Matrix Estimation
Version: 1.0
Date: 2018-05-31
Authors@R: person("Matt", "Galloway", email = "gall0441@umn.edu", role = c("aut", "cre"))
Description: Estimates a lasso penalized precision matrix via the blockwise coordinate descent (BCD). This package is a simple wrapper around the popular 'glasso' package that extends and enhances its capabilities. These enhancements include built-in cross validation and visualizations. See Friedman et al (2008) <doi:10.1093/biostatistics/kxm045> for details regarding the estimation method.
URL: https://github.com/MGallow/CVglasso
BugReports: https://github.com/MGallow/CVglasso/issues
License: GPL (>= 2)
ByteCompile: TRUE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: stats, parallel, foreach, ggplot2, dplyr, glasso
Depends: doParallel
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-05-31 23:30:18 UTC; Matt
Author: Matt Galloway [aut, cre]
Maintainer: Matt Galloway <gall0441@umn.edu>
Repository: CRAN
Date/Publication: 2018-06-04 08:42:55 UTC

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Package antaresRead updated to version 2.1.2 with previous version 2.1.1 dated 2018-05-02

Title: Import, Manipulate and Explore the Results of an 'Antares' Simulation
Description: Import, manipulate and explore results generated by 'Antares', a powerful software developed by RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about 'Antares' here : <https://antares.rte-france.com>). You can see the results of several ANTARES studies here : <http://bpnumerique.rte-france.com/>.
Author: Jalal-Edine ZAWAM [aut, cre], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], RTE [cph]
Maintainer: Jalal-Edine ZAWAM <jalal-edine.zawam@rte-france.com>

Diff between antaresRead versions 2.1.1 dated 2018-05-02 and 2.1.2 dated 2018-06-04

 DESCRIPTION                                  |    8 -
 MD5                                          |   30 ++--
 NEWS                                         |    5 
 R/getLinks.R                                 |  181 +++++++++++++--------------
 R/readLayout.R                               |    6 
 inst/doc/antares.html                        |    4 
 inst/doc/antaresH5.html                      |   20 +-
 tests/testthat/helper_init.R                 |   17 ++
 tests/testthat/test-.timeIdToDate.R          |    2 
 tests/testthat/test-extractDataList.R        |    1 
 tests/testthat/test-h5ReadAntares.R          |    2 
 tests/testthat/test-h5_nodata.R              |    2 
 tests/testthat/test-h5_readInputs.R          |    2 
 tests/testthat/test-h5_setSimulationPathH5.R |    3 
 tests/testthat/test-h5_write.R               |    9 +
 tests/testthat/test-setup.R                  |   10 -
 16 files changed, 172 insertions(+), 130 deletions(-)

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